Byungwook Lee

A recurrent inactivating mutation in RHOA GTPase in angioimmunoblastic T cell lymphoma

The molecular mechanisms underlying angioimmunoblastic T cell lymphoma (AITL), a common type of mature T cell lymphoma of poor prognosis, are largely unknown. Here we report a frequent somatic mutation in RHOA (encoding p.Gly17Val) using exome and transcriptome sequencing of samples from individuals with AITL. Further examination of the RHOA mutation encoding p.Gly17Val in 239 lymphoma samples showed that the mutation was specific to T cell lymphoma and was absent from B cell lymphoma. We demonstrate that the RHOA mutation encoding p.Gly17Val, which was found in 53.3% (24 of 45) of the AITL cases examined, is oncogenic in nature using multiple molecular assays. Molecular modeling and docking simulations provided a structural basis for the loss of GTPase activity in the RHOA Gly17Val mutant. Our experimental data and modeling results suggest that the RHOA mutation encoding p.Gly17Val is a driver mutation in AITL. On the basis of these data and through integrated pathway analysis, we build a comprehensive signaling network for AITL oncogenesis.

Accurate quantification of transcriptome from RNA-Seq data by effective length normalization

We propose a novel, efficient and intuitive approach of estimating mRNA abundances from the whole transcriptome shotgun sequencing (RNA-Seq) data. Our method, NEUMA (Normalization by Expected Uniquely Mappable Area), is based on effective length normalization using uniquely mappable areas of gene and mRNA isoform models. Using the known transcriptome sequence model such as RefSeq, NEUMA pre-computes the numbers of all possible gene-wise and isoform-wise informative reads: the former being sequences mapped to all mRNA isoforms of a single gene exclusively and the latter uniquely mapped to a single mRNA isoform. The results are used to estimate the effective length of genes and transcripts, taking experimental distributions of fragment size into consideration. Quantitative RT–PCR based on 27 randomly selected genes in two human cell lines and computer simulation experiments demonstrated superior accuracy of NEUMA over other recently developed methods. NEUMA covers a large proportion of genes and mRNA isoforms and offers a measure of consistency (‘consistency coefficient’) for each gene between an independently measured gene-wise level and the sum of the isoform levels. NEUMA is applicable to both paired-end and single-end RNA-Seq data. We propose that NEUMA could make a standard method in quantifying gene transcript levels from RNA-Seq data.

A High-Dimensional, Deep-Sequencing Study of Lung Adenocarcinoma in Female Never-Smokers

Background Deep sequencing techniques provide a remarkable opportunity for comprehensive understanding of tumorigenesis at the molecular level. As omics studies become popular, integrative approaches need to be developed to move from a simple cataloguing of mutations and changes in gene expression to dissecting the molecular nature of carcinogenesis at the systemic level and understanding the complex networks that lead to cancer development. Results Here, we describe a high-throughput, multi-dimensional sequencing study of primary lung adenocarcinoma tumors and adjacent normal tissues of six Korean female never-smoker patients. Our data encompass results from exome-seq, RNA-seq, small RNA-seq, and MeDIP-seq. We identified and validated novel genetic aberrations, including 47 somatic mutations and 19 fusion transcripts. One of the fusions involves the c-RET gene, which was recently reported to form fusion genes that may function as drivers of carcinogenesis in lung cancer patients. We also characterized gene expression profiles, which we integrated with genomic aberrations and gene regulations into functional networks. The most prominent gene network module that emerged indicates that disturbances in G2/M transition and mitotic progression are causally linked to tumorigenesis in these patients. Also, results from the analysis strongly suggest that several novel microRNA-target interactions represent key regulatory elements of the gene network. Conclusions Our study not only provides an overview of the alterations occurring in lung adenocarcinoma at multiple levels from genome to transcriptome and epigenome, but also offers a model for integrative genomics analysis and proposes potential target pathways for the control of lung adenocarcinoma.

Localizome: a server for identifying transmembrane topologies and TM helices of eukaryotic proteins utilizing domain information

The Localizome server predicts the transmembrane (TM) helix number and TM topology of a user-supplied eukaryotic protein and presents the result as an intuitive graphic representation. It utilizes hmmpfam to detect the presence of Pfam domains and a prediction algorithm, Phobius, to predict the TM helices. The results are combined and checked against the TM topology rules stored in a protein domain database called LocaloDom. LocaloDom is a curated database that contains TM topologies and TM helix numbers of known protein domains. It was constructed from Pfam domains combined with Swiss-Prot annotations and Phobius predictions. The Localizome server corrects the combined results of the user sequence to conform to the rules stored in LocaloDom. Compared with other programs, this server showed the highest accuracy for TM topology prediction: for soluble proteins, the accuracy and coverage were 99 and 75%, respectively, while for TM protein domain regions, they were 96 and 68%, respectively. With a graphical representation of TM topology and TM helix positions with the domain units, the Localizome server is a highly accurate and comprehensive information source for subcellular localization for soluble proteins as well as membrane proteins. The Localizome server can be found at .

ESTpass: a web-based server for processing and annotating expressed sequence tag (EST) sequences

We present a web-based server, called ESTpass, for processing and annotating sequence data from expressed sequence tag (EST) projects. ESTpass accepts a FASTA-formatted EST file and its quality file as inputs, and it then executes a back-end EST analysis pipeline consisting of three consecutive steps. The first is cleansing the input EST sequences. The second is clustering and assembling the cleansed EST sequences using d2_cluster and CAP3 programs and producing putative transcripts. From the CAP3 output, ESTpass detects chimeric EST sequences which are confirmed through comparison with the nr database. The last step is annotating the putative transcript sequences using RefSeq, InterPro, GO and KEGG gene databases according to user-specified options. The major advantages of ESTpass are the integration of cleansing and annotating processes, rigorous chimeric EST detection, exhaustive annotation, and email reporting to inform the user about the progress and to send the analysis results. The ESTpass results include three reports (summary, cleansing and annotation) and download function, as well as graphic statistics. They can be retrieved and downloaded using a standard web browser. The server is available at http://estpass.kobic.re.kr/.

Programming of Plant Leaf Senescence with Temporal and Inter-Organellar Coordination of Transcriptome in Arabidopsis.

RNA-seq analysis of total and small RNAs throughout the lifespan of Arabidopsis leaves revealed that leaf senescence proceeds with tight temporal and distinctive inter-organellar coordination of transcriptomes. Plant leaves, harvesting light energy and fixing CO2, are a major source of foods on the earth. Leaves undergo developmental and physiological shifts during their lifespan, ending with senescence and death. We characterized the key regulatory features of the leaf transcriptome during aging by analyzing total- and small-RNA transcriptomes throughout the lifespan of Arabidopsis (Arabidopsis thaliana) leaves at multidimensions, including age, RNA-type, and organelle. Intriguingly, senescing leaves showed more coordinated temporal changes in transcriptomes than growing leaves, with sophisticated regulatory networks comprising transcription factors and diverse small regulatory RNAs. The chloroplast transcriptome, but not the mitochondrial transcriptome, showed major changes during leaf aging, with a strongly shared expression pattern of nuclear transcripts encoding chloroplast-targeted proteins. Thus, unlike animal aging, leaf senescence proceeds with tight temporal and distinct interorganellar coordination of various transcriptomes that would be critical for the highly regulated degeneration and nutrient recycling contributing to plant fitness and productivity.

Protein comparison at the domain architecture level

BackgroundThe general method used to determine the function of newly discovered proteins is to transfer annotations from well-characterized homologous proteins. The process of selecting homologous proteins can largely be classified into sequence-based and domain-based approaches. Domain-based methods have several advantages for identifying distant homology and homology among proteins with multiple domains, as compared to sequence-based methods. However, these methods are challenged by large families defined by promiscuous (or mobile) domains.ResultsHere we present a measure, called Weighed Domain Architecture Comparison (WDAC), of domain architecture similarity, which can be used to identify homolog of multidomain proteins. To distinguish these promiscuous domains from conventional protein domains, we assigned a weight score to Pfam domain extracted from RefSeq proteins, based on its abundance and versatility. To measure the similarity of two domain architectures, cosine similarity (a similarity measure used in information retrieval) is used. We combined sequence similarity with domain architecture comparisons to identify proteins belonging to the same domain architecture. Using human and nematode proteomes, we compared WDAC with an unweighted domain architecture method (DAC) to evaluate the effectiveness of domain weight scores. We found that WDAC is better at identifying homology among multidomain proteins.ConclusionOur analysis indicates that considering domain weight scores in domain architecture comparisons improves protein homology identification. We developed a web-based server to allow users to compare their proteins with protein domain architectures.

Fabrication of cables for the background-field magnet system of SSTF

The Korea Superconducting Tokamak Advanced Research (KSTAR) device has a fully superconducting magnet system consisting of 16 Toroidal Field (TF) and 14 Poloidal Field (PF) coils. For the test of the KSTAR cable-in-conduit conductor (CICC), an ambient magnetic field of /spl plusmn/8 T with a maximum change rate of 20 T/s is required and a background-field magnet system is being developed for the Samsung Superconductor Test Facility (SSTF). The CICC for PF1-5 is used as the conductor for background-field coils to check the validity of the PF CICC design. Two pieces of cables have been fabricated and the cable has the length of 870 m and the diameter of 20.3 mm. Pitches are 40, 80, 145, and 237 mm at each cabling stage. The void fraction of the CICC is expected to be more than 36%.

Fabrication of Sm1Ba2Cu3O7 coated conductors using the co-evaporation method

We fabricated a coated conductor 7.5 m long and 9 mm wide using a biaxially textured Ni tape. The standard buffer layers, CeO2/Y SZ/CeO2, were used. A thick Sm1Ba2Cu3O7 (SBCO) film was deposited using the co-evaporation method, followed by in situ deposition of an Ag protection layer. The whole length of SBCO film was deposited in a single batch process, which took 7 h. We checked the distribution of critical currents (Ic) by I–V measurements in all the sections comprising the tape. Ic at 77 K was 90–130 A in most parts of the whole length.

Genetic Landscape of Open Chromatin in Yeast

Chromatin regulation underlies a variety of DNA metabolism processes, including transcription, recombination, repair, and replication. To perform a quantitative genetic analysis of chromatin accessibility, we obtained open chromatin profiles across 96 genetically different yeast strains by FAIRE (formaldehyde-assisted isolation of regulatory elements) assay followed by sequencing. While 5∼10% of open chromatin region (OCRs) were significantly affected by variations in their underlying DNA sequences, subtelomeric areas as well as gene-rich and gene-poor regions displayed high levels of sequence-independent variation. We performed quantitative trait loci (QTL) mapping using the FAIRE signal for each OCR as a quantitative trait. While individual OCRs were associated with a handful of specific genetic markers, gene expression levels were associated with many regulatory loci. We found multi-target trans-loci responsible for a very large number of OCRs, which seemed to reflect the widespread influence of certain chromatin regulators. Such regulatory hotspots were enriched for known regulatory functions, such as recombinational DNA repair, telomere replication, and general transcription control. The OCRs associated with these multi-target trans-loci coincided with recombination hotspots, telomeres, and gene-rich regions according to the function of the associated regulators. Our findings provide a global quantitative picture of the genetic architecture of chromatin regulation.